IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_9552.html
   My bibliography  Save this paper

Technology Transfer and Early Industrial Development: Evidence from the Sino-Soviet Alliance

Author

Listed:
  • Michela Giorcelli
  • Bo Li

Abstract

This paper studies the causal effect of technology and knowledge transfers on early industrial development. Between 1950 and 1957, the Soviet Union supported the “156 Projects” in China for building technologically advanced industrial facilities. We exploit idiosyncratic delays in project completion and the unexpected end of the Sino-Soviet Alliance, and show that receiving both Soviet technology and know-how had large, persistent effects on plant performance, while the effects of receiving only Soviet capital goods were short-lived. The intervention generated horizontal and vertical spillovers, and production reallocation from state-owned to privately owned companies since the late 1990s.

Suggested Citation

  • Michela Giorcelli & Bo Li, 2022. "Technology Transfer and Early Industrial Development: Evidence from the Sino-Soviet Alliance," CESifo Working Paper Series 9552, CESifo.
    • Handle: RePEc:ces:ceswps:_9552
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp9552.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jan De Loecker & Frederic Warzynski, 2012. "Markups and Firm-Level Export Status," American Economic Review, American Economic Association, vol. 102(6), pages 2437-2471, October.
    2. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    3. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Papers 2005-W04, Economics Group, Nuffield College, University of Oxford.
    4. Andrews, Donald W.K. & Marmer, Vadim, 2008. "Exactly distribution-free inference in instrumental variables regression with possibly weak instruments," Journal of Econometrics, Elsevier, vol. 142(1), pages 183-200, January.
    5. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    6. Nicholas Bloom & Benn Eifert & Aprajit Mahajan & David McKenzie & John Roberts, 2013. "Does Management Matter? Evidence from India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(1), pages 1-51.
    7. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    8. Klette, Tor Jakob & Griliches, Zvi, 1996. "The Inconsistency of Common Scale Estimators When Output Prices Are Unobserved and Endogenous," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 343-361, July-Aug..
    9. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    10. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    11. Amit Gandhi & Salvador Navarro & David A. Rivers, 2020. "On the Identification of Gross Output Production Functions," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2973-3016.
    12. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    13. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    14. Wooldridge, Jeffrey M., 2009. "On estimating firm-level production functions using proxy variables to control for unobservables," Economics Letters, Elsevier, vol. 104(3), pages 112-114, September.
    15. Greevy, Robert & Silber, Jeffrey H. & Cnaan, Avital & Rosenbaum, Paul R., 2004. "Randomization Inference With Imperfect Compliance in the ACE-Inhibitor After Anthracycline Randomized Trial," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 7-15, January.
    16. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
    17. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Series Working Papers 2005-W04, University of Oxford, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gaspar, Raymond, 2022. "Harnessing Foreign Technology to Improve Firm Performance: Evidence from Philippine Manufacturing Enterprises," ADBI Working Papers 1321, Asian Development Bank Institute.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Simon Pröll & Giannis Karagiannis & Klaus Salhofer, 2019. "Advertising and Markups: The Case of the German Brewing Industry," Working Papers 732019, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    2. Dobbelaere, Sabien & Kiyota, Kozo & Mairesse, Jacques, 2015. "Product and labor market imperfections and scale economies: Micro-evidence on France, Japan and the Netherlands," Journal of Comparative Economics, Elsevier, vol. 43(2), pages 290-322.
    3. repec:zbw:inwedp:732019 is not listed on IDEAS
    4. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    5. Florin Maican & Matilda Orth, 2017. "Productivity Dynamics and the Role of ‘Big-Box’ Entrants in Retailing," Journal of Industrial Economics, Wiley Blackwell, vol. 65(2), pages 397-438, June.
    6. Paul Schrimpf & Michio Suzuki & Hiroyuki Kasahara, 2015. "Identification and Estimation of Production Function with Unobserved Heterogeneity," 2015 Meeting Papers 924, Society for Economic Dynamics.
    7. Yuriy Gorodnichenko, 2007. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," NBER Working Papers 13666, National Bureau of Economic Research, Inc.
    8. Markus Eberhardt & Christian Helmers, 2010. "Untested Assumptions and Data Slicing: A Critical Review of Firm-Level Production Function Estimators," Economics Series Working Papers 513, University of Oxford, Department of Economics.
    9. Sara Amoroso & Bertrand Melenberg & Joseph Plasmans & Mark Vancauteren, 2015. "Productivity, Price- and Wage-Markups: An Empirical Analysis of the Dutch Manufacturing Industry," CESifo Working Paper Series 5273, CESifo.
    10. Aguirregabiria, Victor, 2009. "Econometric Issues and Methods in the Estimation of Production Functions," MPRA Paper 15973, University Library of Munich, Germany.
    11. Hu, Yingyao & Huang, Guofang & Sasaki, Yuya, 2020. "Estimating production functions with robustness against errors in the proxy variables," Journal of Econometrics, Elsevier, vol. 215(2), pages 375-398.
    12. Bruno Merlevede & Angelos Theodorakopoulos, 2018. "Productivity Effects of Internationalisation Through the Domestic Supply Chain: Evidence from Europe," Working Papers of VIVES - Research Centre for Regional Economics 627689, KU Leuven, Faculty of Economics and Business (FEB), VIVES - Research Centre for Regional Economics.
    13. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    14. Petrick, Matin & Kloss, Mathias, 2013. "Identifying Factor Productivity from Micro-data: The case of EU agriculture," Factor Markets Working Papers 144, Centre for European Policy Studies.
    15. Bruno Merlevede & Angelos Theodorakopoulos, 2016. "Productivity effects from inter-industry offshoring and inshoring: Firm-level evidence from Belgium," FIW Working Paper series 165, FIW.
    16. Pröll, Simon & Salhofer, Klaus & Karagiannis, Giannis, 2019. "Advertising and Markups: The Case of the German Brewing Industry," Discussion Papers DP-73-2019, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    17. Carlos D Santos & Luís F Costa & Paulo B Brito, 2022. "Demand, Supply and Markup Fluctuations," The Economic Journal, Royal Economic Society, vol. 132(644), pages 1620-1645.
    18. Bournakis, Ioannis & Tsionas, Mike G., 2023. "A Non-Parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," MPRA Paper 118100, University Library of Munich, Germany.
    19. repec:zbw:iamodp:271870 is not listed on IDEAS
    20. Mathias Kloss & Thomas Kirschstein & Steffen Liebscher & Martin Petrick, 2019. "Robust Productivity Analysis: An application to German FADN data," Papers 1902.00678, arXiv.org, revised Feb 2019.
    21. Lu, Yunguo & Zhang, Lin, 2022. "National mitigation policy and the competitiveness of Chinese firms," Energy Economics, Elsevier, vol. 109(C).
    22. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.

    More about this item

    Keywords

    industrialization; technology transfer; knowledge diffusion; China;
    All these keywords.

    JEL classification:

    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General
    • N34 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: 1913-
    • N64 - Economic History - - Manufacturing and Construction - - - Europe: 1913-
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_9552. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.